Articles tagged with 'perl'

Browsing around on hacker news one day, I came across a link to a paper entitled "A micro-manual for Lisp - Not the whole truth" by John McCarthy, the self-styled discoverer of Lisp. One commentor stated that they have been using this paper for awhile as a code kata, implementing it several times, each in a different language, in order to better learn that language. The other day I was pretty bored and decided that maybe doing that too would be a good way to learn something and aleviate said boredom. My first implementation is in perl, mostly because I don't want to have to learn a new language and lisp at the same time. The basic start is after the jump.

Modern web applications are complicated beasts. They've got database processes, web serving processes, and various tiers of actual application services. The first two generally take care of themselves. PostgreSQL, MySQL, Apache, Nginx, lighttpd, they all have well-understood ways of starting and keeping themselves up and running.

But what do you do if you have a bunch of processes that you need to keep running that aren't well understood? What if they're well-understood to crash once in a while and you don't want to have to babysit them? You need a user space process manager. Zed Shaw seems to have coined this term specifically for the Mongrel2 manual, and it describes pretty accurately what you'd want: some user-space program running above init that can launch your processes and start them again if they stop. Dropping privilages would be nice. Oh, and it'd be cool if it were sysadmin-friendly. Oh, and if it could automatically detect code changes and restart that'd be nifty too.

Note: this article uses the Twitter V1 API which has been shut down. The concepts still apply but you'll need to map them to the new V2 API.

As some of you might know, Twitter provides a streaming API that pumps all of the tweets for a given search to you as they happen. There are other stream variants, including a sample feed (a small percentage of all tweets), "Gardenhose", which is a stastically sound sample, and "Firehose", which is every single tweet. All of them. Not actually all that useful, since you have to have some pretty beefy hardware and a really nice connection to keep up. The filtered stream is much more interesting if you have a target in mind. Since there was such a hubbub about "Lost" a few weeks ago I figured I would gather relevant tweets and see what there was to see. In this first part I'll cover capturing tweets and doing a little basic analysis, and in the second part I'll go over some deeper analysis, including some pretty graphs!

After using Calorific for a month two things have become very clear. First, I need to eat less. Holy crap do I need to eat less. I went on to SparkPeople just to get an idea of what I should be eating, and it told me between 2300 and 2680 kcal. I haven't implemented averaging yet, but a little grep/awk magic tells me I'm averaging 2793 kcal per day. This is too much. So. One thing to work on.

I'm a nerd. I write software for a living. I spend a lot of my day either sitting in a chair in front of a computer, or laying on my couch using my laptop. I'm not what you'd call... athletic. I did start lifting weights about six months ago but that's really just led to gaining more weight, not losing it. A few years back I started counting calories and I lost some weight, and then stopped counting calories and gained it all back. Time to change that.